Biography
Anirudh is a Pre-doctoral Research Fellow at Microsoft, working with the PROSE (Program Synthesis) team, based out of Redmond. He primarily works on data wranging techniques using neuro-symbolic approaches. Anirudh is primarily advised by Dr. Ashish Tiwari, Dr. Sumit Gulwani and Dr. Vu Le at Microsoft. He has a bachelor’s degree from Veermata Jijabai Technological Institute (V.J.T.I.) in Information Technology.
Outside of work, Anirudh enjoys playing the guitar and listening to songs.
Download my CV .
- AI4Code
- Artificial Intelligence
- Information Retrieval
- Program Synthesis
B.Tech. in Information Technology, 2021
Veermata Jijabai Technological Institute, India.
Recent News
[15/04/2024] 🏆 Our paper “Semantically Aligned Question and Code Generation for Automated Insight Generation” is selected as the Best Paper at LLM4Code at ICSE ‘24.
[06/04/2024] 🎓 I will be joining the UToPiA lab at UT Austin in Fall ‘24!
[22/03/2024] Paper on “Semantically Aligned Question and Code Generation for Automated Insight Generation” accepted to LLM4Code at ICSE ‘24.
[07/01/2024] I am serving as a student volunteer at POPL ‘24!
[10/12/2023] Presented my work on TSTR at EMNLP ‘23. Link to the video
Recent Publications
Experience
- Working on incorporation of Natural Language intent into Microsoft products.
- Collaborated with Microsoft Edge team for web-based data extraction tasks to improve product purchasing experience.
- Successfully automated invoice data extraction tasks for the Microsoft IDC Finance team to improve productivity.
- Employed techniques to combat low-resource name entity recognition tasks by employing ML and program synthesis techniques.
- Devised Landmark-based Robust Synthesis (LRSyn), a state-of-the-art interpretable data extraction framework, robust to version changes in data.
- Spearheaded the clustering and landmark detection tasks during the development of LRSyn, and developed a novel fingerprinting technique for images.
- Successfully published our research paper titled “Landmarks and Regions: A Robust Approach to Data Extraction” at the Conference on Programming Languages Design and Implementation 2022, San Diego.
- Collaborated with 30 changemakers to develop a war-crime detection tool using social media channels.
- Fine-tuned a distil-RoBERTa model for binary classification of war crimes
- Spearheaded the development of a novel two stage prediction pipeline for multi-label classification of warcrimes.
- Worked with the On-Device AI team to improve system performance using Reinforcement Learning.
- Built a State-Of-The-Art Multi-Agent Deep Q-network leveraging prioritized experience replay(PER) and time-bound dynamic reward functions
- Designed a landmark agent simulation environment to show proof of concept.
- Coordinated with the product development team to build an ERP application for manufacturing and service-based industries.
- Employed JavaFX for the development of the application and MySQL for database management.
- Followed an agile based product development life cycle with constant interaction with key product owners.
Accomplishments
